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. Author manuscript; available in PMC: 2025 Apr 1.
Published in final edited form as: Alcohol Clin Exp Res (Hoboken). 2024 Feb 28;48(4):715–728. doi: 10.1111/acer.15282

Longitudinal examination of alcohol use motives, item-level protective behavioral strategies, and alcohol-related consequences

Nicole R Schultz 1, Kirstyn N Smith-LeCavalier 2, Katherine Walukevich-Dienst 3, Mark A Prince 4, Mary E Larimer 2,3
PMCID: PMC11292804  NIHMSID: NIHMS2010104  PMID: 38419206

Abstract

Background:

Alcohol misuse among college students is a public health concern. Protective behavioral strategies (PBS) can be used before, during, after, or instead of drinking to reduce alcohol use and negative consequences, but findings on their utility at the aggregate level are mixed. Although recent work has provided important information on the performance of individual PBS items, it is limited by research designs that are cross-sectional, do not examine consequences, or do not examine other important correlates, such as drinking motives. This study examines both the association between item-l evel PBS and alcohol-related negative consequences and the moderating effect of drinking motives longitudinally.

Methods:

College students from two universities (n = 200, 62.5% female, Mage = 20.16) completed the Drinking Motives Questionnaire-Revised, Protective Behavioral Strategies Survey, the Rutgers Alcohol Problem Index, and a measure of the quantity of alcohol use at baseline and 3-month follow-up. Generalized linear models were conducted to assess direct effects of item-level PBS on alcohol-related consequences and the moderating effects of drinking motives.

Results:

Two PBS items were associated with fewer alcohol-related consequences at follow-up, and two items were associated with greater alcohol-related consequences at follow-up. Drinking motives differentially moderated associations between item-level PBS and alcohol-related consequences for a proportion in the sample. Enhancement motives moderated the greatest number of associations, followed by coping, conformity, and social motives. Certain PBS (e.g., drink slowly, rather than gulp or chug) were moderated by several drinking motives, whereas other PBS items were not moderated by any motives.

Conclusion:

Consistent with previous research, some item-level PBS were associated longitudinally with increased negative consequences, and some were associated with decreased negative consequences. Drinking motives, particularly enhancement, moderated several item-level PBS and consequence associations, suggesting that reasons for drinking may be important for understanding the associations between PBS strategies and alcohol-related consequences.

Keywords: college students, drinking motives, harm reduction, longitudinal moderation, protective behaviors

INTRODUCTION

Alcohol misuse and associated negative consequences among college students are significant public health concerns. Among college students aged 18–22 years, 49.3% report past month alcohol use, with 27.4% of those students reporting “binge” drinking, defined as five or more alcoholic drinks for males or four or more alcoholic drinks for females on the same occasion (SAMSHA, 2021). Alcohol misuse is associated with increased risk for a host of preventable consequences, including death and injury, physical and sexual assault, academic or other psychosocial difficulties, and alcohol use disorder (Hingson et al., 2009; Wechsler & Nelson, 2010). Understanding college students’ utilization of protective behavioral strategies (PBS), and how this relates to their reasons for using alcohol, is particularly important to guide prevention and intervention efforts aimed at reducing these alcohol-related risks.

One method of reducing alcohol use and alcohol-related consequences is the utilization of alcohol-related PBS. Broadly defined, alcohol-related PBS are behavioral strategies (e.g., “use a designated driver”) an individual can implement before, during, after, or instead of drinking to reduce or avoid/limit alcohol consumption and alcohol-related consequences (Martens et al., 2005). PBS are typically examined as the total number of PBS used or aggregated subscales of similar strategies, including serious harm reduction (SHR; e.g., “Use a designated driver”), manner of drinking (MOD; e.g., “Avoid mixing different types of alcohol”), and stopping/limiting drinking (SLD; e.g., “Leave the bar/party at a predetermined time”). Among college students, greater PBS use (i.e., greater total score) has been shown to be associated with experiencing fewer alcohol-related consequences (Araas & Adams, 2008; Benton et al., 2004; Pearson, 2013). Yet, examining the total number of PBS limits our ability to understand what types or which specific PBS are associated with reduced alcohol use or alcohol-related consequences, making it difficult to make specific recommendations about what strategies are most effective. In research examining alcohol PBS subscales, current findings reveal inconsistent associations among PBS and alcohol-related outcomes both cross-sectionally and longitudinally (Pearson, 2013; Prince et al., 2013). As a result, we lack understanding of which PBS might demonstrate the most utility in reducing use and alcohol-related consequences. To address this limitation, recent research has examined associations between item-level PBS and alcohol use outcomes (Dekker et al., 2018; Drane et al., 2019; Jongenelis et al., 2016).

While examining item-level PBS has the potential to offer greater insight into the mixed findings in the existing PBS literature, preliminary research on the utility of individual, item-level PBS for reducing alcohol use and alcohol-related consequences also lacks clarity. Specifically, work in this area has found that certain individual strategies are associated with increased alcohol use both cross-sectionally and longitudinally (Dekker et al., 2018; Drane et al., 2019; Jongenelis et al., 2016). For example, one longitudinal study found that the 16 PBS items had varying associations with alcohol use over a 4-week period (Dekker et al., 2018). Results showed greater use of only one PBS item (“count the number of drinks you have”) was significantly related to decreased alcohol use, four items were related to increased use (“ask a friend to let you know when you have had enough to drink” [SLD], “put extra ice in your drink” [SLD], “use a designated driver” [SHR], and “leave drinking venues at a pre-determined time” [SLD]), and the remaining 11 items were not related to use. Another longitudinal study found that among a large sample of adults, greater increases in using the “count the number of drinks” strategy were associated with greater decreases in alcohol consumption over the span of a year (Drane et al., 2019). These findings suggest that certain strategies may be more effective for reducing alcohol consumption (i.e., counting the number of drinks), whereas others may be associated with heavier drinking. While these results suggest that individual PBS may result in differential impacts on alcohol consumption, a notable gap in the literature exists regarding how individual PBS are associated with alcohol-related consequences when controlling for use. This is particularly important as alcohol use alone does not fully account for the variability in alcohol-related consequences (Prince et al., 2018), and indeed, reductions in alcohol use are not always the primary goal of PBS (e.g., “using a designated driver”). Identifying which PBS are useful under which circumstances will optimize prevention and intervention efforts aimed at reducing drinking and/or alcohol-related consequences.

Drinking motives, or the sought-after effects of alcohol, may help explain differential associations between PBS, alcohol use, and alcohol-related consequences. Drinking motives are thought to represent the final pathway to use, and motives are differentially associated with patterns of drinking (Cooper, 1994; Cox & Klinger, 1988). Generally, enhancement (“because it’s fun”) and coping motives (“to forget your worries”), both representing internal sources of reinforcement, tend to be the most consistent predictors of use and consequences, respectively (Bresin & Mekawi, 2021; Martens et al., 2008). Social motives (“because it helps you enjoy a party”) are also frequently endorsed and are associated with moderate to heavy use and less so with negative consequences (Patrick & Terry-McElrath, 2021); findings on conformity motives (“so you won’t feel left out”) have been mixed (Bresin & Mekawi, 2021; Ham & Hope, 2003; Kuntsche et al., 2005). While examination of drinking motives can provide useful information to clarify previous findings in the PBS literature, the bulk of research examining the relations between PBS and drinking motives has focused on the mediating effect of PBS, either at the aggregate or subscale level, on associations between motives and alcohol outcomes (Bravo et al., 2015; Labrie et al., 2011; Madden & Clapp, 2019; Martens et al., 2007a). Broadly, higher motives for drinking are associated with decreased PBS use (Labrie et al., 2011). However, results become less clear when examining specific motive and PBS associations; for example, total PBS use partially mediated relations between positive reinforcement motives (i.e., social and enhancement) and consequences, but not negative reinforcement motives (i.e., coping; Martens et al., 2007a). These studies show that using for different motives is differentially associated with PBS use, which in turn is associated with variations in alcohol-related outcomes.

While mediation is an important step that can tell us why PBS are effective, we lack information on for whom PBS are effective. By understanding for whom specific PBS are effective, nuanced interventions targeting specific PBS based on motives for use could be employed. To the best of our knowledge, only one study has examined the moderating role of drinking motives on relations between PBS and alcohol outcomes. In a cross-sectional study, college students endorsing greater social, coping, and enhancement motives were less likely to use certain individual PBS (e.g., social motives negatively associated with avoiding drinking games). Additionally, individuals reporting greater coping motives and less mean PBS use were more likely to report abuse/dependence consequences (Patrick et al., 2011). Similarly, individuals reporting high conformity motives and less mean PBS use were more likely to report personal and social negative consequences. While these findings suggest that drinking motives affect the utility of PBS broadly, it remains unclear which specific PBS items, if any, are associated with different motivations to drink.

Current study

This study had two aims. Aim 1 sought to extend Dekker et al. (2018), which examined item-level associations between PBS and use, by investigating longitudinal associations between individual PBS items and alcohol-related negative consequences at a 3-month follow-up (controlling for baseline alcohol use). Given the lack of previous work examining individual PBS items and negative consequences, we did not make specific hypothesis about direct associations. We broadly expected that item-level PBS would be negatively associated with alcohol-related consequences when controlling for baseline alcohol use. Aim 2 sought to replicate and extend Patrick et al. (2011) by evaluating if drinking motives moderated longitudinal relations between individual PBS items and negative consequences at 3-month follow-up, controlling for baseline and follow-up alcohol use (i.e., typical weekly quantity of drinks in the past month), sex at birth, and age. Given the number of moderation analyses, we did not make specific hypotheses about individual items. To offer greater detail about the moderating effects of motives on the relation between PBS and consequences, we conducted analyses using a novel Generalized Linear Model technique for discrete data which allows for determination of the percentage of individuals for whom moderating relationships are significant. Using this novel methodology (MaCabe et al., 2022; Mize, 2019), we aimed to identify which PBS items x motives interactions were associated with consequences for the greatest number of participants.

MATERIALS AND METHODS

Participants and procedures

This study was a secondary data analysis of a sample of college students recruited to participate in a randomized controlled trial (RCT) that tested efficacy of a personalized normative feedback intervention (Larimer et al., 2023). College students from two West coast university campuses were randomly selected from Registrar lists to be invited via email to participate from 2010 to 2011; Campus 1 is a midsized private university, and Campus 2 is a large public university. Screening criteria for enrollment into the RCT studies required at least one episode of heavy drinking within the past month (i.e., 4+/5+ drinks in a single occasion for women/men, respectively).

Of the 5998 students invited to the study, 2767 (46.1%) completed the screener (Campus 1 n = 1521; Campus 2 n = 1246). Of these, 1494 (55.5%) met inclusion criteria and were randomized into one of six conditions. For the purpose of this study, we only used data from participants who were randomized into the control condition (n = 248). Of these participants, 13 participants dropped out of the study prior to completing the baseline assessment, and an additional 10 started but did not complete the baseline assessment, leaving a total of 226 participants. An additional 17 were lost to follow-up and nine started but did not complete the 3-month survey. Notably, participants lost to follow-up or who did not complete the 3-month survey were missing 96.89% of outcome data used in analyses and did not significantly differ from those who completed the 3-month survey on baseline drinking quantity, consequences, PBS, motives, or any demographics. Therefore, these participants were removed from the sample leaving an analytic sample of 200 participants (62.5% female, Mage = 20.16, SDage = 1.34). Participants in the sample were 0.5% American Indian/Alaskan Native, 10.5% Asian, 1.5% Native Hawaiian/Pacific Islander, 3.5% Black or African American, 69.5% White/Caucasian, and 12% Multiracial or Other; 13.57% were Hispanic/Latin. Additionally, participants were 1% Bisexual, 2% Lesbian, 96.5% Straight/Heterosexual, and 0.5% Questioning; all participants reported being cisgender.

Analyses include responses at baseline and 3-month follow-up from participants who were screened into the RCT study but randomized to the control condition and therefore received no active treatment components. Participants who were eligible for the RCT studies were immediately redirected to an online baseline survey that included additional items pertaining to alcohol use and related consequences, PBS, and drinking motives (as well as other related constructs). Follow-up surveys asked participants to respond to the same set of items at each timepoint.

Participants were compensated with $15 for the screening survey, $25 for the baseline survey, and $25 for the 3-month follow-up. Participants could also earn a $25 bonus for completing all four waves. Institutional Review Board approval was obtained from both universities where participants were recruited, and a Federal Certificate of Confidentiality was obtained to further protect participants.

Measures

Drinking motives questionnaire, revised (DMQ-R; Cooper, 1994)

Drinking motives were assessed at baseline using the DMQ-R, a 20-item questionnaire that asked participants to rate how often they drink for certain reasons from 0 = almost never/never to 5 = almost always/always. The DMQ-R includes four motive subscales, each of which are computed as a mean score of its comprised items: coping (e.g., “to forget your worries”; M = 2.88, SD = 0.72), social (e.g., “because it helps you enjoy a party”; M = 3.22, SD = 0.78), enhancement (e.g., “because it’s fun”; M = 1.82, SD = 0.81), and conformity (e.g., “so you won’t feel left out”; M = 2.38, SD = 0.73). The DMQ-R subscales have exhibited adequate psychometric properties among college samples (MacLean & Lecci, 2000; Martin et al., 2016) and internal consistency of the subscales was adequate for this study: coping (α = 0.70), social (α = 0.72), enhancement (α = 0.78), and conformity (α = 0.70).

Protective behavioral strategies survey (PBSS; Martens et al., 2005)

At baseline, participants completed the 15-item PBSS, which assesses the degree to which individuals engage in certain behaviors while drinking from 1 = never to 5 = always. Previous research has shown that the PBSS has adequate reliability and validity among college students (Martens et al., 2005, 2007b). Consistent with previous work, all PBS were endorsed on a range from 1 to 5 and the measure maintained adequate internal validity (α = 0.83). Given this study’s focus on the utility of individual PBS items, we examined PBS use at the item level, as in prior work (Dekker et al., 2018).

Rutgers alcohol problem index (RAPI; White & Labouvie, 1989)

At baseline and 3-month follow-up, participants completed the 23-item RAPI, which asks participants to report on the number of times (0 = never to 4 = more than 10 times) certain negative consequences occurred as a result of their alcohol use in the past 3-months. Example items include: “neglected your responsibilities,” “kept drinking when you promised yourself not to,” and “had a bad time.” Endorsed items were summed to create a total score of the number of negative consequences experienced (M = 6.29, SD = 8.78). Psychometric properties have been shown to be adequate in prior studies with college samples (Buckner et al., 2007; Stewart et al., 2001), and in this sample (α = 0.94).

Alcohol use quantity (daily drinking questionnaire, Collins et al., 1985)

Participants reported alcohol use quantity at both baseline and 3-month follow-up. They were presented with information on standard drink amounts for various types of alcohol and asked “consider a typical week during the last month. How much alcohol, on average, (measured in number of drinks), do you drink on each day of a typical week?” They then reported on their typical quantity of alcohol consumed on each day of the week in the past month (“on a typical Monday, I have…”). The number of drinks for each day were summed to estimate the total number of alcoholic drinks consumed on a typical week in the past month. Participants reported a range of 0–101 and average of 12.17 drinks (SD = 12.79) during a typical week during the past month at baseline and a range of 0–85 and average of 11.81 drinks (SD = 11.69) at follow-up. Baseline alcohol use was significantly, positively associated with 3-month follow up use (r = 0.65, p < 0.001).

Data analysis

All analyses were completed using R (R Core Team, 2018) version 4.2.1. We examined descriptive statistics of all measures, examined the direct effects of total PBS on use and alcohol-related consequences, direct effects of item PBS on alcohol-related consequences, and assessed the moderating effect of each motive subscale (i.e., social, coping, enhancement, and conformity) on each item PBS predicting consequences. In the analytic sample, <1% of data were missing and appeared to be missing at random. Given this, missing data was listwise deleted by model.

Direct effects

In order to assess the direct effects of total and item-level PBS on alcohol-related consequences, we used Quasi-Poisson (QP)-specified generalized linear models due to the positive skew and count distribution of the outcome variable. QP models have been recommended for fitting models for substance use data with count outcomes as they perform best under a range of distributional characteristics (Baggio et al., 2018). We first assessed total PBS use at baseline on alcohol-related consequences at 3-month follow-up, controlling for baseline and follow up alcohol use, sex assigned at birth, and age as covariates. Second, we used one model to assess all PBS items predicting alcohol-related consequences at 3-month follow-up controlling for covariates. Correlations between PBS items ranged from −0.104 to 0.696 which falls below the suggested cutoff of 0.80, precluding concern for multicollinearity (Berry & Feldman, 1985). These analyses were completed using the glm function from the stats package (R Core Team, 2018). Model effects were quantified using Incident Rate Ratios (IRRs) and significance of effects was determined using confidence intervals.

Moderation effects (see Appendix 1)

Moderating effects of motives on the relation between item-level PBS and alcohol-related consequences were also assessed using QP generalized linear models controlling for all motives, baseline and follow-up alcohol use quantity, sex assigned at birth, and age as covariates. Separate models were created for each item-PBS and motive combination and models were interpreted using modglm and margplot functions in the modglm package (MaCabe et al., 2022) designed for interpreting nonlinear interaction effects. This approach allows for the examination of interaction effects for each participant by calculating the average interaction effect, range of interaction effects, and proportion of significant interaction effects, and graphs demonstrating variations in the interaction effect across the sample. This approach has been recently recommended as only interpreting product coefficients for nonlinear interaction terms can result in misleading representations of interaction effects (MaCabe et al., 2022; Mize, 2019). To facilitate reporting and interpretation of moderation findings, effects are described as between and within PBS effects. Between PBS, effects refer to comparisons in the moderation effects between strategies for a given motive (e.g., comparisons between “stop drinking at a predetermined time” × social motives and “drink water while drinking alcohol” × social motives interactions), and within PBS, effects refer to comparisons in moderation effects within each specific strategy for all motives (e.g., comparisons in moderation effects between “stop drinking at a predetermined time” × coping motives and “stop drinking at a predetermined time” × social motives).

RESULTS

Descriptive statistics for individual PBS items are listed in Table 1. Throughout the results, associations are described using the labels provided in the table for each PBS item (e.g., PBS1 = “determine not to exceed a set number of drinks”).

TABLE 1.

Summary statistics for protective behavioral strategies.

PBS Mean SD
PBS 1: Determine not to exceed a set number of drinks 2.81 1.24
PBS 2: Alternate alcoholic and nonalcoholic drinks 2.65 1.13
PBS 3: Have a friend let you know when you have had enough 2.49 1.27
PBS 4: Leave the bar/party at a predetermined time 2.35 1.10
PBS 5: Stop drinking at a predetermined time 2.29 1.10
PBS 6: Drink water while drinking alcohol 3.22 1.23
PBS 7: Put extra ice in your drink 2.25 1.17
PBS 8: Avoid drinking games 2.23 1.03
PBS 9: Drink shots of liquor (R) 3.62 1.04
PBS 10: Avoid mixing different types of alcohol 2.66 1.12
PBS 11: Drink slowly, rather than gulp or chug 3.17 0.94
PBS 12: Avoid trying to “keep up” or out-drink others 3.42 1.16
PBS 13: Use a designated driver 4.34 0.94
PBS 14: Make sure that you go home with a friend 4.20 0.99
PBS 15: Know where your drink has been at all times 4.22 1.08
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Note: “(R)” indicates reverse coding. Items 1–7 represent the LSD subscale; items 8–12 represent the MOD subscale; and items 13–15 represent the SHR subscale.

Abbreviation: PBS, protective behavioral strategies.

Direct effects

Total PBS at baseline was significantly associated with fewer alcohol-related consequences at 3-month follow-up (IRR = 0.75, 95% CI: 0.57–0.99) when controlling for covariates. Table 2 shows the model estimates for direct effects of each item-level PBS on alcohol-related consequences. When assessing item-level PBS predicting 3-month consequences and controlling for covariates, four PBS items (all from MOD subscale) at baseline significantly predicted alcohol-related consequences at 3-month follow-up accounting for variation explained by all other PBS in the model. Specifically, PBS 8 (“Avoid drinking games”), PBS 10 (“Avoid mixing different types of alcohol”), PBS 11 (“Drink slowly, rather than gulp or chug”), and PBS 12 (“Avoid trying to “keep up” or out-drink others”). PBS8 (“Avoid drinking games”) and PBS 11 (“Drink slowly, rather than gulp or chug”) predicted fewer consequences at 3-month follow up whereas PBS 10 (“Avoid mixing different types of alcohol”) and PBS 12 (“Avoid trying to ‘keep up’ or out-drink others”) predicted more consequences at 3-month follow-up.

TABLE 2.

Model estimates for direct effects of each item PBS on alcohol-related consequences (ARC).

ARC
Protective behavioral strategy (PBS) Incidence rate ratios
(Intercept) 191.69 (14.15–2662.50)***
PBS 1: Determine not to exceed a set number of drinks. 1.10 (0.95–1.27)
PBS 2: Alternate alcoholic and nonalcoholic drinks. 0.95 (0.80–1.12)
PBS 3: Have a friend let you know when you have had enough. 1.00 (0.87–1.15)
PBS 4: Leave the bar/party at a predetermined time. 1.06 (0.89–1.27)
PBS 5: Stop drinking at a predetermined time. 0.95 (0.79–1.15)
PBS 6: Drink water while drinking alcohol. 0.93 (0.81–1.06)
PBS 7: Put extra ice in your drink 0.97 (0.85–1.12)
PBS 8: Avoid drinking games. 0.82 (0.69–0.97) *
PBS 9: Drink shots of liquor. 1.08 (0.95–1.22)
PBS 10: Avoid mixing different types of alcohol. 1.17 (1.02–1.33) *
PBS 11: Drink slowly, rather than gulp or chug. 0.68 (0.57–0.82) ***
PBS 12: Avoid trying to “keep up” or out-drink others. 1.21 (1.03–1.42) *
PBS 13: Use a designated driver. 0.90 (0.76–1.07)
PBS 14: Make sure that you go home with a friend. 0.92 (0.75–1.13)
PBS 15: Know where your drink has been at all times. 0.92 (0.78–1.08)
Baseline alcohol use 0.99 (0.98–1.00)
3-month alcohol use 1.04 (1.02–1.05) ***
Sex assigned at birth 0.96 (0.70–1.33)
Age 0.89 (0.79–1.00)
Observations 198
R2 Nagelkerke 0.977
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Note: Bolded items are statistically significant.

*

p<0.05

**

p<0.01, and

***

p<0.001.

Items 1–7 represent the LSD subscale; items 8–12 represent the MOD subscale; and items 13–15 represent the SHR subscale.

Moderation effects

Between PBS effects

Table 3 shows the average interaction effect, proportion significant, and range for moderation estimates of drinking motives on the relation between item-level PBS on alcohol-related consequences. Between PBS effects are shown vertically in Table 3 (e.g., comparisons between “stop drinking at a predetermined time” × social motives and “drink water while drinking alcohol” × social motives). When examining differences in moderation effects between individual PBS items, enhancement motives moderated the relation between seven PBS items (one SLD, three MOD, and three SHR) at baseline and alcohol-related consequences at follow-up for a percentage of participants (>0%), with percentage of significant effects ranging from <1% (PBS 6: “drink water while drinking alcohol”; SLD) to 71.21% (PBS 12: “avoid trying to ‘keep up’ or out-drink others”; MOD). Stated differently, for most of the sample, reporting more frequent use for enhancement reasons had little to no effect on the relation between PBS 6 (“drink water while drinking alcohol”; SLD) and consequences, as enhancement motives only moderated this association for <1% of participants. However, for PBS 12 (“avoid trying to ‘keep up’ or out-drink others”; MOD), reporting more frequent use for enhancement reasons had a notable effect for a large majority of participants (i.e., 71.21%). Similar results were observed for coping and conformity motives, although fewer associations were found. Specifically, coping motives moderated the relation between three PBS items (two MOD; one SHR) and consequences for a percentage of participants. The percentage of significant effects for participants in the sample ranged from 1% (PBS8: “avoid drinking games”; MOD) to 87.88% (PBS 14: “make sure that you go home with a friend”; SHR). Conformity motives moderated the relation between three PBS items (one MOD and two SHR) and ARC for a percentage of participants, with the percentage of significant effects ranging from 1% (PBS 11: “drink slowly, rather than gulp or chug”; MOD) to 79.80% (PBS 14: “make sure that you go home with a friend”; SHR). Social motives moderated the relation between PBS9 (“drink shots of liquor”—reverse coded; MOD) and alcohol-related consequences for <1% of the sample. All other models with social motives moderating the relation between item PBS and consequences were not significant for any portion of the sample.

TABLE 3.

Average interaction effect, proportion significant, and range for moderation estimates for each drinking motive.

Social
 Coping
 Enhancement
 Conformity
AIE (% IE SIG) [Range of IEs] AIE (% IE SIG) [Range of IEs] AIE (% IE SIG) [Range of IEs] AIE (% IE SIG) [Range of IEs]
PBS 1: Determine not to exceed a set number of drinks 0.208 (0.000%) [0.065 to 1.489] 0.428 (0.000%) [0.051 to 4.276] 0.257 (0.000%) [0.052 to 2.351] −0.047 (0.000%) [−0.429 to −0.004]
PBS 2: Alternate alcoholic and nonalcoholic drinks −0.119 (0.000%) [−0.851 to −0.035] 0.208 (0.000%) [−0.030 to 2.175] 0.177 (0.000%) [0.024 to 1.433] −0.038 (0.000%) [−0.220 to −0.009]
PBS 3: Have a friend let you know when you have had enough −0.062 (0.000%) [−0.528 to −0.017] −0.187 (0.000%) [−1.263 to −0.031] 0.091 (0.000%) [0.017 to 0.701] −0.266 (0.000%) [−1.647 to −0.048]
PBS 4: Leave the bar/party at a predetermined time 0.182 (0.000%) [0.047 to 1.244] 0.736 (0.000%) [−0.030 to 7.699] 0.545 (0.000%) [0.062 to 4.850] 0.358 (0.000%) [0.037 to 2.529]
PBS 5: Stop drinking at a predetermined time −0.438 (0.000%) [−3.161 to −0.101] −0.114 (0.000%) [−0.985 to −0.010] −0.123 (0.000%) [−0.910 to −0.026] −0.378 (0.000%) [−2.717 to −0.059]
PBS 6: Drink water while drinking alcohol 0.130 (0.000%) [0.029 to 0.794] 0.227 (0.000%) [−0.069 to 2.721] 0.429 (0.505%) [0.033 to 3.892] 0.468 (0.000%) [0.030 to 3.335]
PBS 7: Put extra ice in your drink 0.727 (0.000%) [0.093 to 6.139] 0.292 (0.000%) [−0.059 to 3.046] 0.264 (0.000%) [0.027 to 1.950] 0.125 (0.000%) [−0.004 to 1.040]
PBS 8: Avoid drinking games 0.188 (0.000%) [0.015 to 1.342] −0.878 (1.015%) [−7.572 to −0.113] −1.039 (67.005%) [−12.151 to −0.126] −0.264 (0.000%) [−1.989 to −0.029]
PBS 9: Drink shots of liquor −0.776 (0.505%) [−5.187 to −0.143] −0.494 (0.000%) [−5.283 to −0.026 −0.746 (41.919%) [−8.686 to −0.107] −0.379 (0.000%) [−3.033 to −0.062]
PBS 10: Avoid mixing different types of alcohol 0.023 (0.000%) [0.007 to 0.186 −0.019 (0.000%) [−0.371 to 0.174 −0.368 (0.000%) [−3.229 to −0.054] −0.285 (0.000%) [−1.996 to −0.037]
PBS 11: Drink slowly, rather than gulp or chug 0.009 (0.000%) [−0.414 to 0.306] −1.304 (15.152%) [−11.424 to −0.195] −1.110 (47.980%) [−10.662 to −0.220] −0.979 (1.010%) [−7.635 to −0.206]
PBS 12: Avoid trying to “keep up” or out-drink others −0.554 (0.000%) [−4.738 to −0.121] 0.733 (0.000%) [0.080 to 6.320] 0.486 (0.000%) [0.088 to 5.982] −0.122 (0.000%) [−1.102 to −0.011]
PBS 13: Use a designated driver 0.192 (0.000%) [0.044 to 1.378] −0.648 (0.000%) [−7.119 to −0.095] −0.626 (6.566%) [−8.036 to −0.139] −0.655 (0.000%) [−6.892 to −0.122]
PBS 14: Make sure that you go home with a friend −0.500 (0.000%) [−4.923 to −0.088] −1.596 (87.879%) [−22.789 to −0.168] −0.892 (71.212%) [−12.476 to −0.199] −1.349 (79.798%) [−18.124 to −0.251]
PBS 15: Know where your drink has been at all times −0.434 (0.000%) [−3.245 to −0.132] −0.904 (0.000%) [−9.355 to −0.072] −0.604 (4.545%) [−5.978 to −0.140] −0.931 (34.848%) [−9.026 to −0.175]
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Note: Effects that significantly moderated for a portion of the sample are bolded. Items 1–7 represent the LSD subscale; items 8–12 represent the MOD subscale; and items 13–15 represent the SHR subscale.

Abbreviation: AIE, average interaction effect; % IE SIG, percent of significant interaction effects; PBS, protective behavioral strategies; Range of IEs, range of interaction effects.

[Correction added on 06 March 2024, after first online publication: In Table 3, the acronyms at the top of the table, were corrected from ‘[LL CI – UL CI]’ to ‘[Range of IEs]’, the abbreviations ‘LL CI, lower limit confidence interval’ and ‘UL CI, upper limit confidence interval’ were removed, and the abbreviation ‘Range of IEs, range of interaction effects’ was added.]

Figures 1–4 show the moderating effects of motives on item-level PBS and negative consequences relations that were significant for a portion of the sample (all plots are available in supplemental materials). Overall, individuals reporting more using for specific motives more often and infrequent use of a given PBS reported more consequences compared to individuals reporting less frequent use for specific motives. However, more frequent use of an individual PBS reduces the difference in consequences for those with higher versus lower motives. Although this effect was broadly consistent, there were a few effects that deviated from this trend. For example, at low levels of PBS 9 (“drink shots of liquor”—reverse coded; MOD), individuals with low versus high levels of social motives reported similar levels of consequences. However, at higher levels of PBS 9, individuals who reported using for social motives less often reported more consequences while individuals who reported using for social motives more often reported slight reductions in consequences. While this effect is inconsistent with the overall observed trend, it was only significant for <1% of the sample.

FIGURE 1.

FIGURE 1

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Moderating effects of social motives on item-level PBS and negative consequences relations that were significant for a portion of the sample.

FIGURE 4.

FIGURE 4

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Moderating effects of conformity motives on item-level PBS and negative consequences relations that were significant for a portion of the sample.

Within PBS effects

In addition to variability in the percentage of participants with significant moderating effects of each motive across all strategies, results demonstrate a range of significant moderating effects of each motive within each specific strategy. Within PBS, effects are shown horizontally in Table 3 (e.g., “drinking at a predetermined time” × coping motives compared to “stop drinking at a predetermined time” × social motives). The effect of certain PBS on consequences was highly dependent on the motives participants reported. Specifically, the relation between PBS 11 (“drink slowly, rather than gulp or chug”; MOD) and consequences was moderated by 3 of 4 motives for a percentage of the sample; enhancement motives moderated the effect for 47.98% of participants, coping for 15.15%, conformity for <1%, whereas social motives did not moderate. Further, for PBS 14 (“make sure that you go home with a friend”; SHR) and consequences, coping motives moderated the relation for 87.88% of participants, conformity for 79.80%, enhancement for 71.21%, and social for 0%. The relations between three additional PBS items and consequences were moderated by 2 of 4 motives for a percentage of the sample; PBS 8 (“avoid drinking games”; MOD) and consequences was moderated by enhancement motives for 67.01% of participants and coping for 1%, PBS 9 (“drink shots of liquor”—reverse coded; MOD) and consequences was moderated by enhancement motives for 41.92% of participants and social for <1%, and PBS 15 (“know where your drink has been at all times”; SHR) was moderated by conformity motives for 34.85% of participants and enhancement for 4.55%. Two PBS items were moderated by 1 of 4 motives. The relation between PBS 6 (“drink water while drinking alcohol”; SLD) and consequences was moderated by enhancement motives for <1% of participants and the relation between PBS 13 (“use a designated driver”; SHR) and consequences was moderated by enhancement motives for 6.57% of participants. Associations between several PBS and alcohol-related consequences did not significantly vary based on the motives participants reported, including PBS 1, PBS 2, PBS 3, PBS 4, PBS 5, PBS7, PBS 10, and PBS 12 (see Table 1 for item descriptions) as none of the four motives moderated the relation between these PBS and consequences for any portion of the sample (i.e., 0%).

DISCUSSION

This study sought to extend the literature on the association of PBS and alcohol-related consequences in two important ways. First, as previous longitudinal studies have only examined the associations between individual PBS items and alcohol use (Dekker et al., 2018; Drane et al., 2019; Jongenelis et al., 2016), we examined the longitudinal associations between individual PBS items and alcohol-related consequences. This is particularly important given that, at the individual level, certain PBS may not actually reduce alcohol consumption—and in some cases increase alcohol consumption (Dekker et al., 2018). However, it is unknown if the use of individual strategies, despite increased alcohol consumption, is associated with fewer alcohol-related consequences over time, which is arguably the broader goal of PBS. Second, we extended previous literature by examining the moderating role of drinking motives on the association between individual PBS items and alcohol-related consequences longitudinally using state-of-the-science statistical techniques.

Similar to previous literature assessing the effect of individual PBS on alcohol use (Dekker et al., 2018; Drane et al., 2019; Jongenelis et al., 2016), results were inconsistent, and in some cases, certain PBS items were associated with greater alcohol-related consequences at follow-up despite total PBS use being associated with fewer consequences at 3-month follow-up. Specifically, PBS 8 (“avoid drinking games”; MOD) and PBS 11 (“drink slowly, rather than gulp or chug”; MOD) were associated with fewer negative consequences at 3-month follow up; however, PBS 10 (“avoid mixing different types of alcohol”; MOD) and PBS 12 (“avoid trying to ‘keep up’ or out-drink others”; MOD) were associated with more negative consequences after controlling for baseline alcohol use and other covariates at 3-month follow-up. The remaining PBS were not associated with 3-month consequences. Notably, these four individual PBS items belong to the MOD subscale, which has previously been established as negatively associated with use and consequences (Martens et al., 2005; Pearson, 2013). These findings may suggest that certain PBS might be less impactful or even contraindicated (e.g., PBS 10, “avoid mixing different types of alcohol”; MOD and PBS 12, “avoid trying to ‘keep up’ or out-drink others”; MOD).

Although it is unclear whether participants in this study used these PBS simultaneously, independently, and in what context, these results lend support to the notion that examination of individual PBS items may provide more important information than sum or aggregate scores, which has important implications for assessment and intervention. It is possible that individuals may engage in other high-risk drinking behaviors that negate the protective effects of the PBS they have implemented—for example, those who avoid mixing different types of alcohol may still engage in other risky consumption behaviors, such as pregaming or mixing alcohol with other substances. Overall, these findings highlight that individual PBS may be differentially associated with alcohol-related outcomes. Future research, particularly using event-level data, will continue to improve our understanding of the unique, individual associations between specific PBS and alcohol-related outcomes, which can be used to inform prevention and intervention.

While these findings add to the extant literature suggesting few item-level PBS are associated with reduced alcohol use and alcohol-related consequences longitudinally, examination of the moderating effects of drinking motives provides important information on psychosocial factors that may impact the utility of individual PBS. Consistent with previous research (Cooper, 1994; Cox & Klinger, 1988), motives differentially moderated the effect between PBS items and alcohol-related consequences. Also consistent with previous research, enhancement motives moderated effects between the greatest number of PBS items and alcohol-related consequences (i.e., seven PBS items) for a portion of the sample, and social motives moderated the least (i.e., one PBS item). Conformity and coping motives moderated relations between three PBS items and alcohol-related consequences for a portion of the sample, although specific items varied by motive. Notably, most PBS items that were moderated by drinking motives were from the MOD and SHR subscales; only “drink water while drinking alcohol” from the SLD subscale was moderated by enhancement motives. These findings suggest that utilization of PBS items from the MOD and SHR subscales may be more influenced by one’s reasons for drinking compared to SLD; however, additional research is needed to parse out these individual effects. Overall, these findings suggest some motives may have a greater impact on the relation between certain PBS and alcohol-related consequences than others.

Within a single PBS item, there were also differential effects across motives. The associations between certain PBS and consequences varied significantly based on which drinking motive participants reported, whereas relations between other PBS items and consequences were not impacted by motives for any portion of the sample. For example, the relations between PBS 11 (“drink slowly, rather than gulp or chug”; MOD) and PBS 14 (“make sure that you go home with a friend”; SHR) and consequences were moderated by 3 of 4 motives for a portion of the sample, whereas various PBS (i.e., PBS 1, PBS 2, PBS 3, PBS 4, PBS 5, PBS 7, PBS 10, and PBS 12) were not moderated by any motives for any portion of the sample. Notably, of the moderations that were significant for a portion of the sample, most findings demonstrated that at low levels of PBS use for a given strategy, those with higher motives reported more consequences than those with lower motives, and at high levels of PBS use for a given strategy, the differences in consequences between those with higher and lower motives are markedly reduced. These findings suggest that the success of certain PBS may be influenced by one’s reasons for drinking, especially at lower levels of PBS use. Adaptive interventions that provide individualized feedback on PBS skills based on an individual’s intentions to drink on a given occasion may prove useful for reducing alcohol-related harms.

Enhancement emerged as the drinking motive that moderated the greatest number of item PBS on alcohol-related consequences relations for a percentage of participants. Specifically, enhancement motives moderated the association between seven individual PBS items and alcohol-related consequences for a percentage of participants. In addition to moderating the most individual items for a percentage of participants, enhancement motives accounted for many of the moderated associations between individual PBS items and alcohol-related consequences that were significant for the greatest proportion of the sample when compared to other motives. While previous literature suggests that those who use for enhancement reasons typically drink more (Bresin & Mekawi, 2021) and overall use fewer PBS (Patrick et al., 2011), our findings suggest that specific PBS used by individuals with enhancement motives may be effective in reducing alcohol-related consequences. In other words, individuals drinking for enhancement reasons may drink in ways that enhance the positive aspects of drinking while simultaneously engaging in specific strategies to reduce negative consequences (e.g., avoid drinking games). Future studies utilizing assessment methods proximal to drinking (e.g., ecological momentary assessment; EMA) that can capture drinking motives, positive and negative consequences, and alcohol-use outcomes as they occur will be important to reinforce the findings from this study.

Clinical implications

Results from this study highlight the differential effects of drinking motives on the associations between individual PBS and consequences, which has important clinical implications. Previous research has highlighted the importance of individual factors such as age and gender (Dekker et al., 2020), as well as important contextual factors, such as type of drinking day (i.e., heavy vs moderate; Linden-Carmichael et al., 2019) in PBS utilization and efficacy. Our findings suggest that drinking motives are an additional contextual factor that may influence an individuals’ utilization of certain PBS. While this study provides a foundation for examining associations between item-level PBS, drinking motives, and alcohol-related outcomes, these findings need to be replicated in studies utilizing event-level methodologies. If supported, these data could be used to better inform alcohol interventions, as previous research has demonstrated that interventions that provide personalized feedback on relationships between drinking motives and drinking-related outcomes have shown promise for reducing alcohol use and associated negative consequences (Blevins & Stephens, 2016; Carey et al., 2007). With advancements in daily assessment and adaptive interventions capable of providing feedback in near real time, future interventions could provide feedback and PBS skills training in the moment based on young adults’ reported intentions for drinking on a given day, particularly given that young adults typically follow through with the PBS they plan to implement when drinking (Fairlie et al., 2021). Such nuanced interventions may improve long-term outcomes to reduce alcohol-related risks, particularly for those at higher risk.

Limitations and future directions

While this study has several strengths that address important gaps in the literature, several limitations should be addressed in future research. First, this study utilized retrospective self-report measures among a relatively demographically homogenous group of participants who were randomly invited to complete a screening survey to participate in a longitudinal study of their alcohol use and other behaviors (Larimer et al., 2023). As data from this study were based on retrospective self-report at baseline and 3-month timepoints, it is unclear how specific PBS items related to specific drinking motives in the moment to affect specific alcohol-related outcomes. Utilization of momentary assessment measures among a more diverse and broad population (e.g., noncollege students) would provide a more nuanced assessment of PBS and drinking motives in the context of alcohol use as it occurs, which would allow for better development of adaptive interventions to improve utilization of certain PBS based on motivations for use. Second, the statistical approach used in this study provides descriptive, individualized results but does not provide cutoffs for significance values for interaction effects. Although we described a range of statistically significant findings, future work should work to determine a clinically meaningful cutoff for the proportion of the sample demonstrating a significant moderation effect. Third, this study utilized the original PBSS (Martens et al., 2005), which consists of 15 items, as opposed to the more recently validated 20-item PBSS (Madson et al., 2013). Thus, there are several individual PBS items (particularly related to serious harm reduction strategies) for which the association to alcohol-related consequences is unknown. Future studies should continue to assess the impact of more recently validated item-level PBS on alcohol-related consequences. Lastly, while this study controlled for sex assigned at birth and age in all models, future research should directly examine how sex assigned at birth, age, and other demographics may influence the posed research questions.

CONCLUSION

Despite these limitations, this study significantly advances our understanding of the longitudinal impact of PBS strategies on alcohol-related negative consequences. Surprisingly, few item-level PBS were associated with decreased alcohol-related consequences, and several were associated with increased consequences. This study also highlights drinking motives as a potentially salient psychosocial factor impacting the association between PBS and consequences. More frequent use of certain PBS strategies appeared to mitigate harms associated with greater reporting of enhancement motives among a large proportion of the sample. Continued research, particularly using methodologies that can establish temporal proximity, on the general utility of item-level PBS and psychosocial factors that increase or decrease PBS effectiveness will be crucial for developing effective, targeted brief intervention efforts for young adults.

Supplementary Material

Supplementary Material

FIGURE 2.

FIGURE 2

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Moderating effects of coping motives on item-level PBS and negative consequences relations that were significant for a portion of the sample.

FIGURE 3.

FIGURE 3

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Moderating effects of enhancement motives on item-level PBS and negative consequences relations that were significant for a portion of the sample.

ACKNOWLEDGEMENTS

This research was supported by NIAAA R01 AA012547, R56 AA012547, R37 AA012547, and T32 AA007455 (PI: Larimer). Article preparation was also supported by NIAAA F32 AA028667 (PI: Schultz) and F32 AA029589 (PI: Walukevich-Dienst). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

APPENDIX 1

We chose not to conduct alpha corrections on moderation analyses because alpha corrections protect against Type I errors, but risk Type II errors. Bonferroni corrections are overly conservative and risk missing important findings (Perneger, 1998; Rothman, 1990). Applying a Bonferroni correction would bias all effects toward Type II errors, which would only increase the likelihood of failing to capture and describe potentially important specific effects. Stated differently, such corrections would not change the primary conclusion that drinking motives may be a potentially salient psychosocial factor impacting the association between PBS and consequences, but important nuance about the associations between item-level PBS and consequences would be lost, which was a primary aim of this article.

Footnotes

CONFLICT OF INTEREST STATEMENT

The authors declare no competing interests.

SUPPORTING INFORMATION

Additional supporting information can be found online in the Supporting Information section at the end of this article.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material
NIHMS2010104-supplement-Supplementary_Material.docx (3.1MB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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